Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 3 |
Since 2016 (last 10 years) | 3 |
Since 2006 (last 20 years) | 3 |
Descriptor
Elementary School Students | 3 |
Grade 2 | 3 |
Learning Analytics | 3 |
Prediction | 3 |
Academic Achievement | 1 |
Accuracy | 1 |
Artificial Intelligence | 1 |
Bayesian Statistics | 1 |
Benchmarking | 1 |
Computer Software | 1 |
Correlation | 1 |
More ▼ |
Author
Akihito Kamata | 1 |
Cooc, North | 1 |
Doris Baker | 1 |
Eric Larson | 1 |
Filderman, Marissa J. | 1 |
Forthmann, Boris | 1 |
Förster, Natalie | 1 |
Makoto Sano | 1 |
Nathan Gage | 1 |
Souvignier, Elmar | 1 |
Toste, Jessica R. | 1 |
More ▼ |
Publication Type
Reports - Research | 3 |
Journal Articles | 2 |
Speeches/Meeting Papers | 1 |
Education Level
Early Childhood Education | 3 |
Elementary Education | 3 |
Grade 2 | 3 |
Primary Education | 3 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
Early Childhood Longitudinal… | 1 |
What Works Clearinghouse Rating
Forthmann, Boris; Förster, Natalie; Souvignier, Elmar – Journal of Intelligence, 2022
Monitoring the progress of student learning is an important part of teachers' data-based decision making. One such tool that can equip teachers with information about students' learning progress throughout the school year and thus facilitate monitoring and instructional decision making is learning progress assessments. In practical contexts and…
Descriptors: Learning Processes, Progress Monitoring, Robustness (Statistics), Bayesian Statistics
Filderman, Marissa J.; Toste, Jessica R.; Cooc, North – Assessment for Effective Intervention, 2021
Although national legislation and policy call for the use of student assessment data to support instruction, evidence suggests that teachers lack the knowledge and skills required to effectively use data. Previous studies have demonstrated the potential of training for increasing immediate teacher outcomes (i.e., knowledge, skills, and beliefs),…
Descriptors: Grade 2, Elementary School Teachers, Mathematics Instruction, Learning Analytics
Zhongdi Wu; Eric Larson; Makoto Sano; Doris Baker; Nathan Gage; Akihito Kamata – Grantee Submission, 2023
In this investigation we propose new machine learning methods for automated scoring models that predict the vocabulary acquisition in science and social studies of second grade English language learners, based upon free-form spoken responses. We evaluate performance on an existing dataset and use transfer learning from a large pre-trained language…
Descriptors: Prediction, Vocabulary Development, English (Second Language), Second Language Learning